In this research it has been tried to present a novel application of continuous wavelet transform
(CWT) to detect possible periodic seismicity in the Mammoth Mountain volcano (United States)
between the years 1983 and 2012. Data sequences are considered as the number of earthquakes
occurred per month. CWT decomposes a data sequence into wavelet coefficients according to time
and frequency domains simultaneously. These coefficients can be utilized to detect seasonality in
specific portions of a data sequence. Furthermore, the global wavelet spectrum (GWS) is used to
explain time-frequency characteristics of a data sequence, and it provides a robust tool to test
periodic nature in the whole of the data series. Our results show that in the time of interest (1983
– 2012) statistically significant seasonality occurred in particular time intervals. Although the
significant annual modulation can be observed in the seismic activity related to upper 3 km with a
highest rate in summer and fall.